Motion/Performance capture.
When restricting ourselves to human modeling, 4D reconstruction is often referred to as motion capture (MoCap). Marker and scanner based MoCap systems [1]}, [2]}, [3]} are popular in industry, yet inconvenient and expensive. Without expensive sensors, camera-based methods are more applicable but often less competitive. Standard methods rely on a multi-view camera setup and leverage 3D human body models [4]}, [5]}, [6]}, [7]}. Active research problems in the MoCap field include template-free methods [8]}, [9]}, [10]}, single-view depth camera methods [11]}, [12]}, [13]}, monocular RGB video methods [14]}, [15]}, and fine-grained body parts (, hand, hair, face) methods [16]}, [17]}, [18]}, [19]}.
In contrast, this paper studies a more generic class-agnostic setting where multiple different non-rigid objects are reconstructed using one unified framework.
